Next Article in Journal
Object-Based Crop Species Classification Based on the Combination of Airborne Hyperspectral Images and LiDAR Data
Next Article in Special Issue
Combination of Well-Logging Temperature and Thermal Remote Sensing for Characterization of Geothermal Resources in Hokkaido, Northern Japan
Previous Article in Journal
Estimating Land Development Time Lags in China Using DMSP/OLS Nighttime Light Image
Previous Article in Special Issue
A Practical Split-Window Algorithm for Estimating Land Surface Temperature from Landsat 8 Data
Article Menu

Export Article

Open AccessArticle
Remote Sens. 2015, 7(1), 905-921; doi:10.3390/rs70100905

Estimation of Land Surface Temperature under Cloudy Skies Using Combined Diurnal Solar Radiation and Surface Temperature Evolution

School of Environment and Resources, Shanxi University, Taiyuan 030006, China
*
Author to whom correspondence should be addressed.
Academic Editors: Zhao-Liang Li, Richard Müller and Prasad S. Thenkabail
Received: 4 November 2014 / Accepted: 7 January 2015 / Published: 15 January 2015
(This article belongs to the Special Issue Recent Advances in Thermal Infrared Remote Sensing)
View Full-Text   |   Download PDF [9659 KB, uploaded 20 January 2015]   |  

Abstract

Land surface temperature (LST) is a key parameter in the interaction of the land-atmosphere system. However, clouds affect the retrieval of LST data from thermal-infrared remote sensing data. Thus, it is important to determine a method for estimating LSTs at times when the sky is overcast. Based on a one-dimensional heat transfer equation and on the evolution of daily temperatures and net shortwave solar radiation (NSSR), a new method for estimating LSTs under cloudy skies (Tcloud) from diurnal NSSR and surface temperatures is proposed. Validation is performed against in situ measurements that were obtained at the ChangWu ecosystem experimental station in China. The results show that the root-mean-square error (RMSE) between the actual and estimated LSTs is as large as 1.23 K for cloudy data. A sensitivity analysis to the errors in the estimated LST under clear skies (Tclear) and in the estimated NSSR reveals that the RMSE of the obtained Tcloud is less than 1.5 K after adding a 0.5 K bias to the actual Tclear and 10 percent NSSR errors to the actual NSSR. Tcloud is estimated by the proposed method using Tclear and NSSR products of MSG-SEVIRI for southern Europe. The results indicate that the new algorithm is practical for retrieving the LST under cloudy sky conditions, although some uncertainty exists. Notably, the approach can only be used during the daytime due to the assumption of the variation in LST caused by variations in insolation. Further, if there are less than six Tclear observations on any given day, the method cannot be used. View Full-Text
Keywords: land surface temperature; net shortwave solar radiation; diurnal evolution; clouds; geostationary meteorological satellite land surface temperature; net shortwave solar radiation; diurnal evolution; clouds; geostationary meteorological satellite
Figures

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Zhang, X.; Pang, J.; Li, L. Estimation of Land Surface Temperature under Cloudy Skies Using Combined Diurnal Solar Radiation and Surface Temperature Evolution. Remote Sens. 2015, 7, 905-921.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top